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dc.contributor.authorDavis, Alberto
dc.contributor.authorGordillo Castillo, Nelly
dc.contributor.authorMontseny Masip, Eduard
dc.contributor.authorAymerich Martínez, Francisco Javier
dc.contributor.authorLópez Córdova, M.
dc.contributor.authorMejía Muñoz, J.
dc.contributor.authorOrtega, L.
dc.contributor.authorMederos, B.
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.date.accessioned2019-05-09T12:12:22Z
dc.date.available2019-05-09T12:12:22Z
dc.date.issued2018-08-01
dc.identifier.citationDavis-Ortiz, A. [et al.]. Automated detection of parenchymal changes of ischemic stroke in non-contrast computer tomography: a fuzzy approach. "Biomedical signal processing and control", 1 Agost 2018, vol. 45, p. 117-127.
dc.identifier.issn1746-8094
dc.identifier.urihttp://hdl.handle.net/2117/132813
dc.description.abstractThe detection of ischemic changes is a primary task in the interpretation of brain Computer Tomography (CT) of patients suffering from neurological disorders. Although CT can easily show these lesions, their interpretation may be difficult when the lesion is not easily recognizable. The gold standard for the detection of acute stroke is highly variable and depends on the experience of physicians. This research proposes a new method of automatic detection of parenchymal changes of ischemic stroke in Non-Contrast CT. The method identifies non-pathological cases (94 cases, 40 training, 54 test) based on the analysis of cerebral symmetry. Parenchymal changes in cases with abnormalities (20 cases) are detected by means of a contralateral analysis of brain regions. In order to facilitate the evaluation of abnormal regions, non-pathological tissues in Hounsfield Units were characterized using fuzzy logic techniques. Cases of non-pathological and stroke patients were used to discard/confirm abnormality with a sensitivity (TPR) of 91% and specificity (SPC) of 100%. Abnormal regions were evaluated and the presence of parenchymal changes was detected with a TPR of 96% and SPC of 100%. The presence of parenchymal changes of ischemic stroke was detected by the identification of tissues using fuzzy logic techniques. Because of abnormal regions are identified, the expert can prioritize the examination to a previously delimited region, decreasing the diagnostic time. The identification of tissues allows a better visualization of the region to be evaluated, helping to discard or confirm a stroke.
dc.format.extent11 p.
dc.language.isoeng
dc.subjectÀrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica
dc.subjectÀrees temàtiques de la UPC::Informàtica
dc.subject.lcshTransient ischemic attack
dc.subject.lcshFuzzy logic
dc.subject.otherIschemic stroke
dc.subject.otherBrain tissue segmentation
dc.subject.otherFuzzy logic
dc.titleAutomated detection of parenchymal changes of ischemic stroke in non-contrast computer tomography: a fuzzy approach
dc.typeArticle
dc.subject.lemacAtac isquèmic transitori
dc.subject.lemacLògica difusa
dc.contributor.groupUniversitat Politècnica de Catalunya. BIOART - BIOsignal Analysis for Rehabilitation and Therapy
dc.identifier.doi10.1016/j.bspc.2018.05.037
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S1746809418301459
dc.rights.accessOpen Access
local.identifier.drac23215051
dc.description.versionPostprint (author's final draft)
local.citation.authorDavis-Ortiz, A.; Gordillo, N.; Montseny, E.; Aymerich, F.X.; López, M.; Mejía-Muñoz, J.; Ortega, L.; Mederos, B.
local.citation.publicationNameBiomedical signal processing and control
local.citation.volume45
local.citation.startingPage117
local.citation.endingPage127


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